Vehicle localization systems: towards low-cost architectures

Abstract

INS-GPS integration is a fundamental task used to enhance the accuracy of an inertial navigation system alone. However, its implementation complexity has been a challenge to most embedded systems. This paper proposes a low-cost FPGA-based INS-GPS integration system, which consists of a Kalman filter and a soft processor. Moreover, we also evaluate the navigation algorithm on a low-cost ARM processor. Processing times and localization accuracy are compared in both cases for single and double precision floating-point format. Experimental results show the advantages of the FPGA-based approach over the ARM-based approach. The proposed architecture can operate at 100 Hz and demonstrates the advantage of using FPGAs to design low-cost INS-GPS localization systems.

Methodologies and evaluation of electronic travel aids for the visually impaired people: a review

“…Correct altitude is tracked within a short period of 10s. Another sample of navigation assisted by IMU can be seen in [26], [27]. Other than wayfinding, gyroscope sensor is also associated with the ability of balancing and angle determination.…”

A novel map-merging technique for occupancy grid-based maps using multiple robots: a semantic approach

“…On the other hand, map merging can be considered as a subset of the robotic mapping phenomenon. In other respects, map merging is the creation of a consistent global map from local ones that are produced by different agents [13,14,18]. The map-merging problem has dynamic and static approaches.…”